In an indoor positioning system, the location of a wireless device such as a mobile user terminal can be determined with respect to a location network comprising multiple anchor radios. These anchors are wireless nodes whose locations are known a priori, typically being recorded in a location database which can be queried to look up the location of a node. The anchor nodes thus act as reference nodes for location. Measurements are taken of the signals transmitted between the mobile device and a plurality of anchor nodes, for instance the RSSI (receiver signal strength indicator), ToA (time of arrival) and/or AoA (angle of arrival) of the respective signal. Given such a measurement from three or more nodes, the location of the mobile terminal may then be determined relative to the location network using techniques such as trilateration, multilateration or triangulation. Given the relative location of the mobile terminal and the known locations of the anchor nodes, this in turn allows the location of the mobile device to be determined in more absolute terms, e.g. relative to the globe or a map or floorplan.
As well as indoor positioning, other types of positioning system are also known, such as GPS or other satellite-based positioning systems in which a network of satellites acts as the reference nodes. Given signal measurements from a plurality of satellites and knowledge of those satellites' positions, the location of the mobile device may be determined based on similar principles.
The determination of the device's location may be performed according to a “device-centric” approach or a “network-centric” approach. According to a device centric approach, each reference node emits a respective signal which may be referred to as a beacon or beaconing signal. The mobile device takes measurements of signals it receives from the anchor nodes, obtains the locations of those nodes from the location server, and performs the calculation to determine its own location at the mobile device itself. According to a network-centric approach on the other hand, the anchor nodes are used to take measurements of signals received from the mobile device, and an element of the network such as the location server performs the calculation to determine the mobile device's location. Hybrid or “assisted” approaches are also possible, e.g. where the mobile device takes the raw measurements but forwards them to the location server to calculate its location.
One application of a positioning system is to automatically provide a wireless mobile device with access to control of a utility such as a lighting system, on condition that the mobile device is found to be located in a particular spatial region or zone associated with the lighting or other utility. For instance, access to control of the lighting in a room may be provided to a wireless user device on condition that the device is found to be located within that room and requests access. Once a wireless user device has been located and determined to be within a valid region, control access is provided to that device via a lighting control network. Other examples of location based services or functionality include for example payment of road tolls at toll booths or other location dependent payments.
As well as just trilateration, multilateration or triangulation, techniques now exist which determine the location of mobile device based on a “fingerprint” of a known environment. The fingerprint comprises a set of data points each corresponding to a respective one of a plurality of locations in the environment in question. Each data point is generated during a training phase by taking a measurement of the signals received from any reference nodes that can be heard at the respective location (e.g. a measure of signal strength such as RSSI) and storing this in a location server along with the coordinates of the respective location. The data point is stored along with other such data points in order to build up a fingerprint of the signal measurements as experienced at various locations within the environment.
Once deployed, the signals measurements stored in the fingerprint can then be compared with signal measurements currently experienced by a mobile user device whose location is desired to be known, in order to estimate the location of the mobile device relative to the corresponding coordinates of the points in the fingerprint. For example this may be done by approximating that the device is located at the coordinates of the data point having the closest matching signal measurements, or by interpolating between the coordinates of a subset of the data points having signal measurements most closely matching those currently experienced by the device.
The fingerprint can be pre-trained in a dedicated training phase before the fingerprint is deployed by systematically placing a test device at various different locations in the environment. Alternatively or additionally, the fingerprint can built up dynamically by receiving submissions of signal measurements experienced by the actual devices of actual users in an ongoing training phase.
One such fingerprint-based technique is disclosed in “Utilization of User Feedback in Indoor Positioning System”; A. K. M. Mahtab Hossain, Hien Nguyen Van and Wee-Send Soh; Pervasive and Mobile Computing (PMC), Elsevier, vol. 6, no. 4, pp. 467-481, August 2010 [Hossain et al]. When the user's location can be known by other means than the fingerprint, this location is fed back to a location server along with the currently experienced signal measurements in order to dynamically build a fingerprint of the environment. The location feedback may be explicit or implicit. Explicit feedback means the user knows his or her own actual location and submits this via a user interface, e.g. the user points to the known location on a user interface comprising a map or plan of the environment. Implicit feedback on the other hand is taken without the user being aware. Implicit feedback according to Hossain occurs when the user encounters certain landmarks as he or she goes about his or her business or daily routine, the locations of the landmarks being fixed and known to the system. For example when the user uses a card reader, the fact that the user was encountered at the known location of the card reader is automatically submitted to the location server along with the signal measurements experienced by that user's mobile device.
According to Hossain et al, each location is also stored in association with a weight w intended as a measure of the credibility of the location. The weight is taken into account in the fingerprint-based positioning algorithm such that points with a lower credibility are given less weight in determining the location of a device from the fingerprint.